Changes in tissue types are manifested in ultrasound propagation as changes in acoustic properties, which in turn lead to the bright echoes from the interfaces. In the case of tumors, the interior tissue is generally a homogeneous mixture of viable cancer cells, capillaries, connective tissue and necrotic cells. The amount of necrosis can provide some valuable clues to the viability of the tumor, itself.
Conventionally, since capillaries are the sites of the vital interchange of blood nutrients and cellular metabolites in healthy tissue, a measurement of vascularity may be used as an indicator of tissue viability, often calling for excision of a treated section of tissue for histopathology. The tissue is stained for vascular endothelia, usually the stain CD31, and the microvascular density (MVD) is measured under a microscope. The MVD is a standard measurement of the efficacy of angiogenic and anti-angiogenic drugs. Additionally, optical microscopy can also be used to image and measure the amount of dead, or necrotic tissue within a tumor.
Typical histopathology analysis of a tumor involves removal of the tumor from the animal, fixing the tumor with a fixative agent, usually Neutral Buffered Formalin (NBF) or ethanol (ETOH), and examining the specimen one thin slice at a time. This conventional approach necessarily requires more specimens (i.e. animals) than a longitudinal experiment over time, and is very labor intensive.
Necrosis in tissue occurs as a result of a fatal injury to a cell. Cells, upon death, elicit an inflammatory response and quickly deteriorate. Cell structure disintegrates, cell walls break down (lyse) and the fragmented cell contents, including nuclear material, spill into the interstitial spaces between the cells. Necrotic tissue even appears different from viable cells under the microscope, and it is recognizable by the complete absence of structure. Necrosis is histologically identified by the structure of the tissue using stains differential to nucleic proteins. However, histopathology is necessarily post-mortem, and a longitudinal analysis of the tumor over time is not possible.
Additionally, cancer treatments that target the cells increase the regions of necrosis around the intratumoral blood vessels. The presence of necrosis can therefore be used to analyze such characteristics as tumor morphology, tumor angiogenesis and efficacy of anti-cancer therapy; however, the study of these metrics has traditionally been done using optical microscopy and histopathology biomarkers. In laboratory research, where the number of animals used for research can be quite large, histopathology measurements are time consuming, expensive and require terminating the study of the subject. Additionally, tissue fixing can result in damage to some aspect of the tumor and loss of information.
As indicated above, past study of tumors and development of anti-cancer therapies have primarily relied on terminating the study at specified time points and performing histological tests on the excised tumor. This process is time consuming, requires the use of a large number of subjects, and necessarily precludes the use of longitudinal measurements on the same tumor. In addition to the statistical problems posed by the lack of repeated measurements, the histological analysis of tumors is done using microscopically thin slices of the tumor, providing information on a very limited region, in a non-realtime manner.
Ultrasonic imaging techniques are widely used in imaging portions of the body, including analysis of tumors. Changes in tissue types are manifested in ultrasound propagation as changes in acoustic properties, which in turn lead to the bright echoes from the interfaces.
Clinical ultrasound instruments can be classified into two broad categories: Continuous Wave and Pulsed Wave. Continuous Wave ultrasound is used primarily for its Doppler capabilities as an audio aid to detect flowing blood. Pulsed ultrasound is used for imaging, and nearly all modern pulsed wave ultrasound devices employ color representations of blood flow (CD) to associate movement to a pixel.
Ultrasound imaging equipment has made significant improvements, and now has capabilities that were not possible only a few years ago. With an increase in frequency and resolution, it is now possible to use ultrasound in a number of clinical settings that were previously reserved only for X-ray imaging. Increased resolution and decreased noise can now provide clear images able to detect details that would have, in many situations, required extensive interpretation in the past. In the late 1980's and early 1990's, ultrasonic tissue characterization had mixed results due to the characteristic coherent interference phenomenon known as “speckle”. With the improvement in devices and the increase in ultrasound frequency, also came an increase in the bandwidth with concomitant speckle reduction. The engineering advances in clinical ultrasound equipment can now allow tissue characterization, at least in research environments that were previously reserved for special instrumentation.
The ultrasound image is characterized by pixels of differing intensities that may be used to differentiate different regions of interest. Additionally, some tissue types can be subjectively identified by their texture. Intensities of the necrotic core of a tumor are brighter than the viable border tissue, for example. Observing necroses obtained from histopathologic sampling under the microscope and correlating the observed features with the corresponding ultrasound images, shows that there is a coarse texture to the necrotic regions, as illustrated in FIG. 1, which shows a B16-F10 tumor stained for CD34. FIG. 1(a) shows a region of healthy tumor cells, and FIG. 1(b) shows a region of necrosis.
In the case of tumors, the interior tissue is generally a homogeneous mixture of viable cancer cells, capillaries, connective tissue and necrotic cells. As mentioned above, the amount of necrosis can provide some valuable clues to the viability of the tumor, itself. Tumor cells lack the normal, programmed cell-death mechanisms that keep normal cells in check. However, tumor cells, like all living cells, can die if exposed to a fatal environment. For a new tumor without medical intervention, the cells farthest away from the peritumoral regions and outside the perfusion range of newly formed microvasculature die from lack of oxygen and nutrients.
The ability of ultrasound to discriminate between viable and necrotic tumor regions has previously been accomplished using the ultrasound backscatter microscope (UBM). The necrotic core of a tumor spheroid is known to be detectable using very high ultrasound frequencies. There are morphological differences between the two regions, as determined by histopathology. In a very high frequency (e.g., 100 MHz) ultrasound image, the necrotic core appears as a bright circular region in the middle of the tumor spheroid, because of the increased density of nuclei. However, such high frequency ultrasound devices are relatively expensive, and are not readily available in clinical settings, in comparison to lower frequency devices, e.g., devices operating in the 4–12 MHz region, for example.
There are three primary characteristics of tissue that can increase backscattered energy, and result in brighter pixels in the resulting image:    1. the number of scattering bodies;    2. the reflectivity of the scattering bodies; and    3. the spatial distribution of scattering bodies within the resolved area of the image.
However, previous efforts in analyzing image pixel data to place the pixels into one of two groups, e.g., necrotic tissue and viable tissue, have used conventional univariate approaches, as shown in FIG. 2, which provides a flowchart of a conventional univariate K-Means segmentation algorithm for normally distributed clusters. Such an approach relies upon a relatively simple univariate statistical “distance” related to the difference between an intensity value of a particular pixel, and the “average” or mean intensity value representative of a group of pixels. Unfortunately, and as determined by the use of histopathologic sampling and training images, this univariate approach results in a higher probability of misclassifying a significant portion of the various pixels into the wrong class. Further, univariate statistical analysis of image pixel data increases the probability of both Type I and Type II errors, along with the misclassification of pixels.
What is needed then is an apparatus and method that allows more powerful statistical test of differences over time, and which includes the repeated longitudinal measurement of a tumor as it progresses in a single subject.
What is further needed is an apparatus and method for ultrasound imaging, using multiple image characteristics, to provide a means of performing non-histopathologic longitudinal segmentation of an image, including identification and differentiation of tumor necrosis and viable tissue.
What is still further needed is an apparatus and method for multivariate analysis of necroses using tissue differentiation based on pixel gray-scale values, augmented by differences in texture to increase the power of the statistical analysis and lower the incidence of misclassification of the different tissue types.